Search Results (1,495)

This study used the Q methodology to examine how Korean science, technology, engineering, and mathematics (STEM) students perceive the experience of reading classical texts and how such experiences relate to their overall well-being. We developed 31 statements for the Q-sorting process and collected data from 39 undergraduate students majoring in science, technology, engineering, and mathematics (STEM). The analysis identified three distinct perception types: type 1—exploratory type, which broadens thinking through diverse perspectives, type 2—experience type, which shares achievement and enjoyment through reading together, and type 3—insight type, which seeks universal values and truth. These findings suggest that, for science and engineering students, reading classics offers a multidimensional experience—encompassing intellectual expansion, relational engagement, and philosophical reflection—beyond conventional academic activities. In particular, the therapeutic dimension of reading, as discussed in bibliotherapy, has emerged as a mechanism that supports self-reflection and emotional resilience. Although each type approached classical reading differently, the participants demonstrated varied perceptions that reflect dimensions of well-being, such as emotional awareness, relational connection, and self-reflection, as expressed through the Q-sorting of pre-defined statements. Based on these results, this study concludes that classical reading can function as a significant mechanism for promoting well-being, offering new directions and practical implications for classical reading education. Full article

Background and Objectives: Hysterectomy is a common non-obstetric procedure. Minimally invasive techniques, such as laparoscopy and robot-assisted surgery, have replaced open surgery for benign gynecologic conditions. Robotic surgery offers reduced blood loss and shorter hospital stays but is limited by high costs. Articulating laparoscopic instruments aim to replicate robotic dexterity cost-effectively. However, comparative data on these two approaches in hysterectomy are limited. Materials and Methods: This multicenter study analyzed the outcomes of hysterectomies for benign gynecological diseases using articulating laparoscopic instruments (prospectively recruited) and robot-assisted surgery (retrospectively reviewed). The surgeries were performed by minimally invasive gynecological surgeons in South Korea, Japan, and Taiwan. The baseline characteristics, operative details, and outcomes, including operative time, blood loss, complications, and hospital stay, were compared. Statistical significance was set at p < 0.05. Results: A total of 151 patients were analyzed, including 67 in the articulating laparoscopy group and 84 in the robot-assisted group. The operating times were comparable (114.9 vs. 119.9 min, p = 0.22). The articulating group primarily underwent dual-port surgery (79.1%), whereas the robot-assisted group required four or more ports in 71.4% of the cases (p < 0.001). Postoperative complications occurred in both groups, without a significant difference (9.0% vs. 3.6%, p = 0.17). No severe complications or significant differences in the 30-day readmission rates were observed. Conclusions: Articulating laparoscopic instruments provide outcomes comparable to robot-assisted surgery in hysterectomy while reducing the number of ports required. Further studies are needed to explore the learning curve and long-term impact on surgical outcomes. Full article

The complex system of high-entropy materials makes it challenging to reveal the specific function of each site for oxygen evolution reaction (OER). Here, with nickel foam (NF) as the substrate, FeCoNiCrMo/NF is designed to be prepared by metal–organic frameworks (MOF) as a precursor under an argon atmosphere. XRD analysis confirms that it retains a partial MOF crystal structure (characteristic peak at 2θ = 11.8°) with amorphous carbon (peaks at 22° and 48°). SEM-EDS mapping and XPS demonstrate uniform distribution of Fe, Co, Ni, Cr, and Mo with a molar ratio of 27:24:30:11:9. Electrochemical test results show that FeCoNiCrMo/NF has excellent OER characteristics compared with other reference prepared samples. FeCoNiCrMo/NF has an overpotential of 285 mV at 100 mA cm⁻² and performs continuously for 100 h without significant decline. The OER mechanism of FeCoNiCrMo/NF further reveal that Co and Ni are true active sites, and the dissolution of Cr and Mo promote the conversion of active sites into MOOH following the lattice oxygen mechanism (LOM). The precipitation–dissolution equilibrium of Fe also plays an important role in the OER process. The study of different reaction sites in complex systems points the way to designing efficient and robust catalysts. Full article

Porcine circovirus type 2 (PCV2) is a globally prevalent swine pathogen that induces immunosuppression, predisposing pigs to subclinical infections. In intensive farming systems, PCV2 persistently impairs growth performance and vaccine efficacy, leading to substantial economic losses in the swine industry. Emerging evidence suggests that certain viruses exploit Suppressor of Cytokine Signaling 3 (SOCS3), a key immune checkpoint protein, to subvert host innate immunity by suppressing cytokine signaling. While SOCS3 has been implicated in various viral infections, its regulatory role in PCV2 replication remains undefined. This study aims to elucidate the mechanisms underlying the interplay between SOCS3 and PCV2 during viral pathogenesis. Porcine SOCS3 was amplified using RT-PCR and stably overexpressed in PK-15 cells through lentiviral delivery. Bioinformatics analysis facilitated the design of three siRNA candidates targeting SOCS3. We systematically investigated the effects of SOCS3 overexpression and knockdown on PCV2 replication kinetics and host antiviral responses by quantifying the viral DNA load and the mRNA levels of cytokines. PCV2 infection upregulated SOCS3 expression at both transcriptional and translational levels in PK-15 cells. Functional studies revealed that SOCS3 overexpression markedly enhanced viral replication, whereas its knockdown suppressed viral proliferation. Intriguingly, SOCS3-mediated immune modulation exhibited a divergent regulation of antiviral cytokines: PCV2-infected SOCS3-overexpressing cells showed elevated IFN-β but suppressed TNF-α expressions, whereas SOCS3 silencing conversely downregulated IFN-β while amplifying TNF-α responses. This study unveils a dual role of SOCS3 during subclinical porcine circovirus type 2 (PCV2) infection: it functions as a host-derived pro-viral factor that facilitates viral replication while simultaneously reshaping the cytokine milieu to suppress overt inflammatory responses. These findings provide novel insights into the mechanisms underlying PCV2 immune evasion and persistence and establish a theoretical framework for the development of host-targeted control strategies. Although our results identify SOCS3 as a key host determinant of PCV2 persistence, the precise molecular pathways involved require rigorous experimental validation. Full article

Peatlands store substantial amounts of carbon (C) in the form of peat, but are increasingly threatened by drought and shrub encroachment under climate warming. However, how peat decomposition and its temperature sensitivity (Q₁₀) vary with depth and plant litter input under these stressors remains poorly understood. We incubated peat from two depths with different degrees of decomposition, either alone or incubated with Sphagnum divinum shoots or Betula ovalifolia leaves, under five temperature levels and two moisture conditions in growth chambers. We found that drought and Betula addition increased CO₂ emissions in both peat layers, while Sphagnum affected only shallow peat. Deep peat alone or with Betula exhibited higher Q₁₀ than pure shallow peat. Drought increased the Q₁₀ of both depths’ peat, but this effect disappeared with fresh litter addition. The CO₂ production rate showed a positive but marginal correlation with microbial biomass carbon, and it displayed a rather similar responsive trend to warming as the microbial metabolism quotient. These results indicate that both deep and dry peat are more sensitive to warming, highlighting the importance of keeping deep peat buried and waterlogged to conserve existing carbon storage. Additionally, they further emphasize the necessity of Sphagnum moss recovery following vascular plant encroachment in restoring carbon sink function in peatlands. Full article

Investigating the factors influencing rice grain yield (GY) is critical for optimizing nitrogen (N) management and enhancing resource use efficiency in rice cultivation. However, few studies have comprehensively investigated the factors affecting rice GY, considering an entire influence chain encompassing rice N uptake, growth indicators, and GY components. In this study, field experiment with six different N fertilizer rates (0, 60, 120, 180, 225, and 300 kg N ha⁻¹, i.e., N0, N60, N120, N180, N225, and N300) was conducted in the Jianghan Plain in the Middle Reaches of the Yangtze River, China, to comprehensively elucidate the factors influencing rice GY from aspects of rice N uptake, growth indicators, and GY components and determine the optimal N fertilizer rate. The results showed that rice GY and N uptake initially increased and then either stabilized or declined with higher N fertilizer rate, while apparent N loss escalated with increased N fertilizer rate. The application of N fertilizer significantly promoted the increase in straw N uptake, which was significantly positively correlated with growth indicators (p < 0.05). Among all GY components, panicle number per hill was the most significant positive factor influencing rice GY, and it was significantly positively correlated with all rice growth indicators (p < 0.05). In addition, N180 was the optimal N fertilizer rate, ensuring more than 95% of maximum GY and reducing N loss by 74% and 39% compared to N300, respectively. Meanwhile, the average N balance for N180 remained below 60 kg N ha⁻¹. In conclusion, optimizing the N fertilizer application in paddy fields can effectively maintain stable rice GY and minimize environmental pollution. Full article

This paper investigates the well-posedness of the inverse problem for the time-fractional Burgers equation, which aims to reconstruct initial conditions from terminal observations. Such equations are crucial for the modeling of hydrodynamic phenomena with memory effects. The inverse problem involves inferring initial conditions from terminal observation data, and such problems are typically ill-posed. A framework based on optimal control theory is proposed, addressing the ill-posedness via $H^1$ regularization. Three substantial results are achieved: (1) a rigorous mathematical framework transforming the ill-posed inverse problem into a well-posed optimization problem with proven existence of solutions; (2) theoretical guarantee of solution uniqueness when the regularization parameter is $\alpha >0$ and the stability is of order O($\delta$) with respect to observation noise ($\delta$); and (3) the discovery of a “super-stability” phenomenon in numerical experiments, where the actual stability index (0.046) significantly outperforms theoretical expectations (1.0). Finally, the theoretical framework is validated through comprehensive numerical experiments, demonstrating the accuracy and practical effectiveness of the proposed optimal control approach for the reconstruction of hydrodynamic initial conditions. Full article

To address the decline in measurement accuracy of magnetometers due to process errors and environmental interference, as well as the insufficient robustness of traditional calibration algorithms under strong interference conditions, this paper proposes an ellipsoid fitting algorithm based on Dynamic Adaptive Elite Particle Swarm Optimization (DAEPSO). The proposed algorithm integrates three enhancement mechanisms: dynamic stratified elite guidance, adaptive inertia weight adjustment, and inferior particle relearning via Lévy flight, aiming to improve convergence speed, solution accuracy, and noise resistance. First, a magnetometer calibration model is established. Second, the DAEPSO algorithm is employed to fit the ellipsoid parameters. Finally, error calibration is performed based on the optimized ellipsoid parameters. Our simulation experiments demonstrate that compared with the traditional Least Squares Method (LSM) the proposed method reduces the standard deviation of the total magnetic field intensity by 54.73%, effectively improving calibration precision in the presence of outliers. Furthermore, when compared to PSO, TSLPSO, MPSO, and AWPSO, the sum of the absolute distances from the simulation data to the fitted ellipsoidal surface decreases by 53.60%, 41.96%, 53.01%, and 27.40%, respectively. The results from 60 independent experiments show that DAEPSO achieves lower median errors and smaller interquartile ranges than comparative algorithms. In summary, the DAEPSO-based ellipsoid fitting algorithm exhibits high fitting accuracy and strong robustness in environments with intense interference noise, providing reliable theoretical support for practical engineering applications. Full article

Background and Objectives: COVID-19 may have long-term adverse effects on bone health, particularly in individuals aged ≥50 years with obesity or diabetes, who are predisposed to impaired bone quality. Materials and Methods: This retrospective cohort study used TriNetX data from 141 healthcare organizations across North America and Western Europe. Patients aged ≥50 years with overweight (body mass index 25–30 kg/m²), obesity (body mass index ≥ 30 kg/m²), or type 2 diabetes (T2DM) and COVID-19 (2019–2024) were propensity score-matched to non-COVID-19 controls. Exclusion criteria included prior overweight, obesity, diabetes, osteoporosis, T-score ≤ −2.5, Z score ≤ −2.0, fractures, pneumonia, tuberculosis, and cancer. Outcomes included new-onset osteoporosis, fragility fractures, and low T-scores (≤−2.5). Cox regression estimated hazard ratios (HRs); sensitivity analyses assessed lag effects (1–4 years). Results: Among 327,933 matched pairs, COVID-19 was linked to increased osteoporosis risk at 3 years (HR, 1.039; 95% CI, 1.003–1.077) and 6 years (HR, 1.095; 95% CI, 1.059–1.133). Sensitivity analysis showed rising risk with longer lag times: HRs were 1.212, 1.379, 1.563, and 1.884 at 1 to 4 years, respectively. Subgroup analyses confirmed consistent trends. Conclusions: COVID-19 is independently associated with elevated long-term osteoporosis risk in older adults with new-onset overweight, obesity, or T2DM, peaking at 4 years post-infection and persisting through 6 years. Full article

Recent major advancements in cryo-electron microscopy (cryo-EM) have enabled high-resolution structural analysis, accompanied by developments in image processing software packages for single-particle analysis (SPA). SPA facilitates the 3D reconstruction of proteins and macromolecular complexes from numerous individual particles. In this study, we systematically evaluated the impact of symmetry parameters and particle quantity on the 3D reconstruction efficiency using the dihydrolipoyl acetyltransferase (E2) inner core of the pyruvate dehydrogenase complex (PDC). We specifically examined how inappropriate symmetry constraints can introduce structural artifacts and distortions, underscoring the necessity for accurate symmetry determination through rigorous validation methods such as directional Fourier shell correlation (FSC) and local-resolution mapping. Additionally, our analysis demonstrates that efficient reconstructions can be achieved with a moderate particle number, significantly reducing computational costs without compromising structural accuracy. We further contextualize these results by discussing recent developments in SPA workflows and hardware optimization, highlighting their roles in enhancing reconstruction accuracy and computational efficiency. Overall, our comprehensive benchmarking provides strategic insights that will facilitate the optimization of SPA experiments, particularly in resource-limited settings, and offers practical guidelines for accurately determining symmetry and particle quantity during cryo-EM data processing. Full article

The utilization of iron tailings in road construction poses significant environmental risks due to the complex release mechanisms of pollutants and varying regional conditions. This study integrates an exponential decay model with an instantaneous pollutant transport model, employing Monte Carlo simulations to assess risks and regional characteristics. Results show high Potential Hazard Indices (PHIs) for arsenic, manganese, barium, nickel, and lead, with PHI values between 4.2 and 22.7. Simulations indicate that manganese and nickel concentrations may exceed groundwater standards, particularly in humid areas. The study recommends controlling the iron tailings mixing ratio based on climate, suggesting limits of 35% in humid, 60% in semi-humid, and more lenient ratios in arid and semi-arid regions. It also underscores the need for improved risk assessment methodologies and region-specific management strategies at the national level. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains among the most lethal malignancies, with a five-year survival rate below 12%, largely attributable to its asymptomatic onset, late-stage diagnosis, and limited curative treatment options. Although PDAC accounts for approximately 3% of all cancers, it is projected to become the second leading cause of cancer-related mortality in the United States by 2030. A major contributor to its dismal prognosis is the lack of validated early detection strategies for asymptomatic individuals. In this review, we present a comprehensive synthesis of current advances in the early detection of PDAC, with a focus on the identification of high-risk populations, novel biomarker platforms, advanced imaging modalities, and artificial intelligence (AI)-driven tools. We highlight high-risk groups—such as those with new-onset diabetes after age 50, pancreatic steatosis, chronic pancreatitis, cystic precursor lesions, and hereditary cancer syndromes—as priority populations for targeted surveillance. Novel biomarker panels, including circulating tumor DNA (ctDNA), miRNAs, and exosomes, have demonstrated improved diagnostic accuracy in early-stage disease. Recent developments in imaging, such as multiparametric MRI, contrast-enhanced endoscopic ultrasound, and molecular imaging, offer improved sensitivity in detecting small or precursor lesions. AI-enhanced radiomics and machine learning models applied to prediagnostic CT scans and electronic health records are emerging as valuable tools for risk prediction prior to clinical presentation. We further refine the Define–Enrich–Find (DEF) framework to propose a clinically actionable strategy that integrates these innovations. Collectively, these advances pave the way for personalized, multimodal surveillance strategies with the potential to improve outcomes in this historically challenging malignancy. Full article

Urban traffic congestion poses persistent challenges to mobility, public safety, and governance efficiency in metropolitan areas. This study proposes an intelligent traffic flow forecasting framework based on an extended Long Short-Term Memory (xLSTM) model, specifically designed for real-time congestion prediction and proactive police dispatch support. Utilizing a real-world dataset collected from over 300 vehicle detector (VD) sensors, the proposed model integrates vehicle volume, speed, and lane occupancy data at five-minute intervals. Methodologically, the xLSTM model incorporates matrix-based memory cells and exponential gating mechanisms to enhance spatio-temporal learning capabilities. Model performance is evaluated using multiple metrics, including congestion classification accuracy, F1-score, MAE, RMSE, and inference latency. The xLSTM model achieves a congestion prediction accuracy of 87.3%, an F1-score of 0.882, and an average inference latency of 41.2 milliseconds—outperforming baseline LSTM, GRU, and Transformer-based models in both accuracy and speed. These results validate the system’s suitability for real-time deployment in police control centers, where timely prediction of traffic congestion enables anticipatory patrol allocation and dynamic signal adjustment. By bridging AI-driven forecasting with public safety operations, this research contributes a validated and scalable approach to intelligent transportation governance, enhancing the responsiveness of urban mobility systems and advancing smart city initiatives. Full article

Sperm freezability exhibits marked individual variability, yet the mechanisms remain unclear. Using bulls as the experimental model, we integrated proteomic (sperm) and metabolomic (seminal plasma) analyses of high-freezability (HF) and control (CF) bulls to identify key biomarkers associated with sperm freezability. Post-thaw motility and membrane integrity were significantly higher in HF bulls (p < 0.05). Sperm proteome analysis revealed upregulated antioxidant proteins (PRDX2, GSTM4), heat shock proteins (HSP70, HSP90), and key enzymes in arginine and proline metabolism (PRODH, LAP3). Seminal plasma metabolomics revealed elevated spermine in HF bulls. Meanwhile, we found that spermine abundance was positively correlated with post-thaw motility, as well as with the expression levels of both PRODH and LAP3 (r > 0.6, p < 0.05). Functional validation demonstrated that 200 μM spermine supplementation in cryopreservation extenders enhanced post-thaw motility, kinematic parameters (VAP, VSL, VCL), membrane integrity, and acrosome integrity (p < 0.05). Concurrently, spermine enhanced antioxidant enzyme (SOD, CAT, GSH-Px) activity and reduced ROS and MDA levels (p < 0.05). Our study reveals a spermine-driven antioxidant network coordinating sperm–seminal plasma synergy during cryopreservation, offering novel strategies for semen freezing optimization. Full article